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High Foundation Models · 1 min read

Orca: learning GPT-4 reasoning through explanation traces

In one sentence Microsoft Research trains Orca 13B on step-by-step GPT-4 explanations (explanation traces), outperforming ChatGPT on BigBench and AGIEval with 13 billion parameters.

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Most open-source models learn by imitating only the final answers of larger models. Orca does something different: it also learns the reasoning that leads to the answer, by reading the step-by-step explanations GPT-4 provides when solving a problem.

It's like the difference between copying the math homework and watching how the teacher solves each step on the board.

The result is a 13-billion-parameter model that, on certain complex reasoning tests, beats much larger models including ChatGPT.

Companies

Microsoft

Tools

Orca, GPT-4

Tags

OrcaMicrosoftImitation LearningGPT-4BigBench

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